Powered by NVIDIA for Serious Performance

At the heart of the ZGX Nano is the NVIDIA GB10 Grace Blackwell Superchip. This advanced chip delivers up to 1000 TOPS of AI compute and includes 128GB of unified memory. It’s a serious step up from most desktop setups and can handle AI models up to 200 billion parameters on its own.

If your team is working on even more complex workloads, the ZGX Nano has room to grow. HP made it easy to link two units, giving you the ability to scale your compute without rebuilding your entire workflow. That kind of flexibility is rare in a system that fits neatly on your desk.

Work Locally Without Compromise

What makes the ZGX Nano especially valuable is how it supports AI work where it actually happens. Instead of waiting in a queue for cloud resources – or navigating approval processes for external data storage – teams can do more locally. You get immediate access to GPU power, and you stay in full control of your data.

And when that data is sensitive, local compute is even more important. Whether you’re in finance, government, healthcare, or enterprise research, keeping proprietary information on-premises is often a requirement. The ZGX Nano meets that need while still giving you the performance you expect from remote servers.

Tools That Keep Teams Moving

Each system comes with AI Studio, a development environment designed to help teams manage resources, track experiments, and collaborate more efficiently. It simplifies the day-to-day aspects of model development so teams can stay focused on the work that matters.

Secure Storage for Heavy Lifting

With up to 4TB of encrypted local NVMe storage, you can keep large datasets and model checkpoints close and secure. That’s especially useful if you’re managing multiple experiments or working across different client environments.

Real-World Flexibility for Real Teams

Let’s look at a few real-world examples:

· A software company building AI-powered customer support tools can run natural language models on the ZGX Nano and iterate quickly on product features.

· A university lab developing models for medical research can maintain patient data locally and comply with strict privacy guidelines.

· A startup exploring image recognition or video analysis can reduce its cloud spending and reinvest those savings into product development.

Because the ZGX Nano is compact and quiet, it works well in a wide range of settings. There’s no need to redesign your office or build out a dedicated server room. This workstation is plug-and-play, and it’s built to work as hard as you do.

Purpose-Built for AI

Every aspect of the ZGX Nano design—from the memory architecture to the software tools—is built to support AI and machine learning workflows. Whether your team is developing models from scratch or fine-tuning existing ones, the ZGX Nano is designed to keep up with your pace.

Get Ready for Launch

While this system hasn’t officially launched yet, it’s expected to arrive soon. We expect strong interest across industries, especially from teams that are already looking for ways to speed up development and manage compute costs more effectively.

If you’d like to be among the first to know when the HP ZGX Nano AI Station becomes available, reach out today. We’ll make sure you’re on the list for updates and help you decide whether this system is the right fit for your next phase of AI work.

For teams that want speed, security, and flexibility—without compromise—the HP ZGX Nano could be the solution you’ve been waiting for

Poly Certifications:

• • Introduction to Poly PLYOS102
  • Poly Headset Fundamentals (HEDFND)
  • Poly Headset Sales Exam (HEDSALES-EX)

HPE Certifications:

• • HPE Certified AI As-a Service Solutions
  • HPE Certified Aruba Networking Solutions 
  • Aruba Campus Access Certification 
  • HPE Solution Certified – Private Cloud AI

CrowdStrike Certifications:

• • CrowdStrike Technical Sales Accreditation
  • CrowdStrike Sales Accreditation

Ericsson Certifications:

• • Ericsson Cradlepoint Mountaineer
  • Ericsson Enterprise Wireless Mountaineer Pre-Sales
  • Ericsson Enterprise Wireless Certified Network Professional

Other Certifications:

• •  Discover: Technical Certification
  • Google Cloud SecOps Technical Certification
  • Forcepoint DLP – Sales Associate
  • VMWare 2X Certified Professional DCV & NV

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Why AI Can’t Always Wait for the Cloud

Large-scale AI models require enormous amounts of processing power, memory, and bandwidth. And while public cloud services offer scale, they also introduce challenges: long provisioning times, rising costs, and performance constraints when latency matters.

Modern AI applications—like fine-tuning models on proprietary datasets, real-time inference, or running simulations—demand local, immediate performance. They need compute resources to be where the data is, not a region away.

Local Workstations Are Stepping In

AI workstations are becoming the go-to option for teams who need data center-level performance without relying exclusively on the data center. Systems like HP’s Z8 Fury and Z8 G5, equipped with up to four NVIDIA RTX™ 6000 Ada GPUs, deliver 192GB of GPU memory and nearly 6 petaflops of AI compute.

With that kind of power, teams can:

• Train models on sensitive internal data—without exporting it

• Run multiple GPU-heavy apps at once (simulation, modeling, rendering)

• Handle real-time decision-making and inferencing at the edge

• Accelerate exploration, testing, and deployment with local control

Where Local AI Is Already Making a Difference

Architecture, Engineering & Construction (AECO):
AI-enhanced design workflows demand rapid iteration. Local workstations let teams test energy models, structural simulations, and generative layouts in real time.

Manufacturing:
Digital twins, layout optimization, and predictive maintenance all benefit from GPU-powered compute on-site—especially when time and precision are critical.

Creative & Media Production:
AI is now embedded in editing, rendering, and effects pipelines. From Redshift to Unreal Engine, content creators rely on local horsepower to keep projects moving without delays.

Data Science & AI Research:
Fast model development depends on tight feedback loops. Workstations give teams a consistent, responsive environment with preloaded tools like PyTorch, TensorFlow, and RAPIDS via the Z by HP Data Science Stack Manager.

The Hybrid Future: Smarter, Not Bigger

Workstations don’t replace the cloud. But they offer a smarter approach to hybrid infrastructure—one that gives IT teams more control over cost, performance, and security.

• Run sensitive or performance-intensive workloads locally

• Shift to cloud or data center when scale demands it

• Empower remote teams through secure access with HP Anyware

This balance reduces cloud dependency while maximizing agility. And it ensures that AI infrastructure adapts to the task—not the other way around.

Designed for IT, Built for Business

IT leaders need reliable, secure, and manageable infrastructure that doesn’t slow innovation. NVIDIA RTX™-powered Z by HP workstations are ISV-certified, remotely manageable, and built to run 24/7 in professional environments.

With HP Anyware, teams can securely access powerful Z workstations from anywhere—giving hybrid and remote users the same performance they’d expect in the office.

And with HP Wolf Security, your AI and data workflows are protected from BIOS to browser, reducing risk while maintaining compliance.

Final Word: Ready for What AI Demands Next

AI isn’t slowing down, and neither should your infrastructure. The demands of generative tools, data-heavy simulations, and edge inferencing require more than just available compute—they require the right compute, in the right place, at the right time.

HP’s Z workstations, powered by NVIDIA RTX™, offer a proven solution: local performance, enterprise reliability, and scalable flexibility. For IT leaders navigating the next wave of AI adoption, that’s a foundation worth building on. Contact us to learn more.